An approach to working up cases of embolic stroke of undetermined source

Background--from a therapeutic viewpoint,it is important to differentiate the underlying causes of embolism in patients with cryptogenic stroke,such as aortic arch atheroma,patent foramen ovale,and paroxysmal atrial fibrillation. we investigated the clinical and radiological characteristics of these 3 common causes of cryptogenic embolism to develop models for decision making in etiologic workups. methods and results--a total of 321 consecutive patients with acute infarcts from cryptogenic embolism were included. patients were divided into 3 groups-aortic arch atheroma (n=40),patent foramen ovale (n=153),and paroxysmal atrial fibrillation (n=128) -based on extensive cardiologic workups. we used a multinomial logistic regression analysis to detect the clinical and diffusionweighted imaging factors associated with the probability of aortic arch atheroma,patent foramen ovale,and paroxysmal atrial fibrillation. clinical and radiological features differed among the groups. the patent foramen ovale group had a healthy vascular risk factor profile and showed posterior circulation involvement compared with other groups (p<0.01). in contrast,paroxysmal atrial fibrillation-related strokes had higher initial national institutes of health stroke scale (nihss) scores and larger lesions than the other groups (p<0.001). the aortic arch atheroma group had clinical features similar to those of the paroxysmal atrial fibrillation group but showed small lesions scattered in multiple vascular territories (p<0.001). multivariate regression analysis revealed that age,initial nihss score,lesion size (≥20 mm),multiple (≥3) lesions,and involvement of posterior circulation or multiple vascular territories differentiated the 3 groups (pseudo,r2=0.656). the prediction ability of this model was validated in the external validation cohort (n=117,area under the curve 0.78). conclusions--our data indicate that patients with cryptogenic embolic stroke show distinct clinical and radiological features depending on the underlying causes. © 2016 the authors.